Sensing and Modeling Human Behaviors In Complex Conversational Scenes

Understanding human behavior has been an intriguing topic studied by many disciplines, including social science, neuroscience, etc. Humans exhibit social behaviors, through for example, interacting, conversing, empathizing with each other. Systematically and scientifically studying these behaviors often requires granular observations and...

Exponential Word Embeddings: Models and Approximate Learning

The digital era floods us with an excessive amount of text data. To make sense of such data automatically, there is an increasing demand for accurate numerical word representations. The complexity of natural languages motivates to represent words with high dimensional vectors. However, learning in a high dimensional space is challenging when the...

Models for supervised learning in sequence data

Much of the observational data that we see around is, is ordered in space or time. For instance, video data, audio data or text data. This ordered data, called sequence data, calls for automatic analysis using supervised learning. Traditional single-observation supervised learning is challenged by sequence data, because (1) the length of...